Pasqui, M. (2015). Evaluation of future diurnal variability and projected changes in extremes of precipitation and temperature and their impacts on crop production over regional case studies (e.g. Agroscenari case studies) (Vol. 6).
Abstract: The daily weather of the four decades were used as input to EPIC simulation model to test the effects on crop yield, crop evapotranspiration, number of days with water and nitrogen stress in the silage maize -Italian ryegrass irrigated cropping systems in the Oristanese case study area.The monthly DTR (diurnal temperature range) pattern predicted for the FC (future climate, 2020-2030) indicates that spring and summer months are the most sensitive to DTR increase. The increase ryegrass yield simulated by EPIC under FC was interpreted as the positive effects on increased temperature on the winter-spring grass growth rates. The decreased production of maize was attributed to a shortening of the crop cycle, which reduced the intercepted radiation. The simulations run to assess the pure effect of DTR shift indicated almost no effects on crop yield but significant effects on crop evapotranspiration, whose increase observed under FC was largely associated to DTR, particularly in maize. The stochastic generation of daily weather with WXGEN indicates a sufficient accuracy for average DTR patterns and the central part of the daily DTR distribution, while the range of absolute values increased substantially, in relation to the increased probability of extremes in one century vs one decade.(Abstract supplied by the publisher) No Label
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Dono, G., Cortignani, R., Dell’Unto, D., Doro, L., Lacetera, N., Mula, L., et al. (2014). Productive and economic adaptation of Mediterranean agriculture to climate change (Produktive und wirtschaftliche Anpassung der mediterranen Landwirtschaft an den Klimawandel). In Jahrbuch der ÖGA (Vol. 24, pp. 213–222).
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Tomozeiu, R., Pasqui, M., & Quaresima, S. (2017). Future changes of air temperature over Italian agricultural areas: a statistical downscaling technique applied to 2021–2050 and 2071–2100 periods. Meteorology and Atmospheric Physics, in press.
Abstract: Climate change scenarios of seasonal minimum and maximum temperature over different Italian agricultural areas, during the periods 2021–2050 and 2071–2100 against 1961–1990, are assessed. The areas are those selected in the framework of the Agroscenari project and are represented by: Padano–Veneta plain, Marche, Beneventano, Destra Sele, Oristano, Puglia and Sicilia, all areas of prominent agricultural vocation with excellence productions. A statistical downscaling technique applied to ENSEMBLES global climate simulations, emission scenario A1B, is used to achieve this objective. The statistical scheme consists of a multivariate regression based on Canonical Correlation Analysis. The scheme is constructed using large-scale fields derived from ECMWF reanalysis and seasonal mean minimum, maximum temperature derived from national observed daily gridded data that cover 1959–2008 period. Once the most skillful model has been selected for each season and variable, this is then applied to GCMs of ENSEMBLES runs. The statistical downscaling method developed reveals good skill over the case studies of the present work, underlying the possibility to apply the scheme over whole Italian peninsula. In addition, the results emphasize that the temperature at 850 hPa is the best predictor for surface air temperature. The future projections show that an increase could be expected to occur under A1B scenario conditions in all seasons, both in minimum and maximum temperatures. The projected increases are about 2 °C during 2021–2050 and between 2.5 and 4.5 °C during 2071–2100, respect to 1961–1990. The spatial distribution of warming is projected to be quite uniform over the territory to the end of the century, while some spatial differences are noted over 2021–2050 period. For example, the increase in minimum temperature is projected to be slightly higher in areas from northern and central part than those situated in the southern part of Italian peninsula, during 2021–2050 period. The peak of changes is projected to appear during summer season, for both minimum and maximum temperature. The probability density function tends to shift to warmer values during both periods, with increases more intense during summer and to the end of the century, when the lower tail is projected to shift up to 3 °C and the upper tail up to 6 °C. All these projected changes have important impacts on viticulture, intensive fruit and tomatoes, some of the main agricultural systems analyzed in the Agroscenari project.
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Nguyen, T., Mula, L., Cortignani, R., Seddaiu, G., Dono, G., Virdis, S., et al. (2016). Perceptions of present and future climate change impacts on water availability for agricultural systems in the western Mediterranean region. Water, 8(11), 523 (18 pp).
Abstract: Many Mediterranean countries have experienced water shortages during the last 20 years and future climate change projections foresee further pressure on water resources. This will have significant implications for irrigation water management in agricultural systems in the future. Through qualitative and quantitative empirical research methods carried out on a case study on four Mediterranean farming systems located in Oristano, Italy, we sought to understand the relationship between farmers’ perceptions of climate change (i.e., increased temperature and decreased precipitation) and of present and future water availability for agriculture as forecasted by climatic and crop models. We also explored asymmetries between farmers’ perceptions and present and future climate change and water scenarios as well as factors influencing perceptions. Our hypotheses were that farmers’ perceptions are the main drivers of actual water management practices and that sustainable practices can emerge from learning spaces designed from the understanding of the gaps between perceptions and scientific evidences. Results showed that most farmers perceived that climate change is occurring or will occur in their area. They also perceived that there has been an increased temperature trend, but also increased precipitation. Therefore, they are convinced that they have and will have enough irrigation water for agriculture in the near future, while climate change projections foresee an increasing pressure on water resources in the Mediterranean region. Such results suggest the need for (i) irrigation management policies that take into account farmers’ perceptions in order to promote virtuous behaviors and improve irrigation water use efficiency; (ii) new, well-designed learning spaces to improve the understanding on climate change expectations in the near future in order to support effective adaptive responses at the farm and catchment scales.
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Dono, G., Cortignani, R., Doro, L., Giraldo, L., Ledda, L., Pasqui, M., et al. (2013). An integrated assessment of the impacts of changing climate variability on agricultural productivity and profitability in an irrigated Mediterranean catchment. Water Resource Manage., 27(10), 3607–3622.
Abstract: Climate change is likely to have a profound effect on many agricultural variables, although the extent of its influence will vary over the course of the annual farm management cycle. Consequently, the effect of different and interconnected physical, technical and economic factors must be modeled in order to estimate the effects of climate change on agricultural productivity. Such modeling commonly makes use of indicators that summarize the among environmental factors that are considered when farmers plan their activities. This study uses net evapotranspiration (ETN), estimated using EPIC, as a proxy index for the physical factors considered by farmers when managing irrigation. Recent trends suggest that the probability distribution function of ETN may continue to change in the near future due to changes in the irrigation needs of crops. Also, water availability may continue to vary due to changes in the rainfall regime. The impacts of the uncertainties related to these changes on costs are evaluated using a Discrete Stochastic Programming model representing an irrigable Mediterranean area where limited water is supplied from a reservoir. In this context, adaptation to climate change can be best supported by improvements to the collective irrigation systems, rather than by measures aimed at individual farms such as those contained within the rural development policy.
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